1 to 25 of 58 Permanent Neural Network Jobs in England

turn ideas into reality. If you're passionate about pushing the boundaries of AI, we want you on board! Job Description We are seeking an experienced Neural Network Optimization Engineer who will specialize in enhancing the performance, latency, and throughput of neural network inference workflows. The ideal candidate will have substantial hands-on experience … You will collaborate closely with ML researchers to ensure that our machine learning models run at peak efficiency and reliability in production environments. Key Responsibilities Optimize neural network models for inference performance and latency reduction Benchmark, analyze, and improve inference performance on targeted hardware platforms. Collaborate with the ML researchers to deploy optimized models in production environments. … Stay updated with the latest developments in model optimization, inference engines, quantization methods, and related technologies. Requirements Proven professional experience optimizing neural network inference workloads. Strong expertise with TensorRT, Triton language, CUDA programming. Experience with neural network quantization techniques. Proficiency in Python and PyTorch. Deep understanding of GPU architectures and performance optimization. Excellent problem More ❯

Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG's mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency. What you … least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar Solid background in one or more of the following: (i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design; (ii) design and test of advanced convolutional … recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner; (iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar Desired qualifications: Publications, e.g. in top-tier conferences and journals: IEEE Transactions More ❯

including AI/Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow More ❯

systems Exposure/experience in containerization technologies like docker, Kubernetes, AWS EKS etc. Proficiency in ML algorithms, such as multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. More ❯

design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing). Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks. Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios. Proficiency in Python (for More ❯

leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture Experience with graph machine learning (i.e. graph neural networks, graph data science) and practical applications thereof This is complimented by your experience working with Knowledge Graphs, ideally biological, and a familiarity with biological ontologies Experience with complex More ❯

data visualisation skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More! More information: Enjoy fantastic More ❯

deliver our projects efficiently and effectively. The Data Scientist role combines data and analytics with applications knowledge. We make extensive use of advanced techniques including LLMs, Computer Vision; Neural Networks; NLP and advanced statistics. Education Qualification (Minimum) Bachelor's Degree in a STEM subject (typically, but not limited to: Maths; Physics; Physical/Engineering Sciences; Data Science; Computer More ❯

world problems; Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale More ❯

via APIs Familiarity with data visualization tools Knowledge of locating, assessing and integrating third party data-sets Experience with machine learning techniques and libraries (e.g., regression, classification, clustering, neural networks). Solid understanding of AI concepts, including supervised and unsupervised learning. Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure) Education and Knowledge Bachelor's or Master's More ❯

engineers, and business units to deliver value. Write high-quality Python code following best practices. Continuously research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data More ❯

Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure … record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems More ❯

environment. A background leading Data Science teams in an eCommerce or conversion rate optimisation-focused environment is a plus. Hands-on experience with Machine & Deep Learning, AI and Neural Networks tools including Python, Spark, Tensor Flow. Competencies across core programming language including Python, Java, C/C++, R. That you can work in a cross-functional environment, managing More ❯

Generation (RAG) methods Solve industry relevant problems Design and implement artificial intelligence systems and applications that can simulate human intelligence processes through the creation and validation of algorithms, neural networks, and other machine learning techniques. Collaborate with cross-functional teams to ensure seamless integration of software components. Stay updated with the latest trends and advancements in the Technology More ❯

Generation (RAG) methods Solve industry relevant problems Design and implement artificial intelligence systems and applications that can simulate human intelligence processes through the creation and validation of algorithms, neural networks, and other machine learning techniques. Collaborate with cross-functional teams to ensure seamless integration of software components. Stay updated with the latest trends and advancements in the Technology More ❯

and a growth mindset. What You’ll Do Design, build, and scale machine learning models using environmental and observational data. Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods. Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets. Work cross-functionally with science More ❯

e.g., Python, Java, C#). 2+ years of experience in the production deployment of Automation Anywhere A360 bots. Knowledge and understanding of Generative AI techniques, including deep learning, neural networks, and natural language processing. Familiarity with process analysis and improvement methodologies. Excellent problem-solving skills and attention to detail. Ability to work collaboratively in a team environment and More ❯

Other services require a good working knowledge of Databricks, Logic Apps, and the Power Platform knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc) and their real-world advantages/drawbacks knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc) experience with the More ❯

Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep More ❯

Woven by Toyota, we are at the forefront of developing advanced Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep More ❯

and maintaining complex models using tools such as Excel, R and SQL. Hands-on involvement in delivering complex, multi-disciplinary modelling projects, including the development of neural network models. Practical application of AI/ML techniques in industrial process optimisation and predictive analytics Demonstrated ability to take on divers roles across the lifecycle of complex modelling initiatives More ❯

and maintaining complex models using tools such as Excel, R and SQL. Hands-on involvement in delivering complex, multi-disciplinary modelling projects, including the development of neural network models. Practical application of AI/ML techniques in industrial process optimisation and predictive analytics Demonstrated ability to take on divers roles across the lifecycle of complex modelling initiatives More ❯

Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science, Actuarial Science More ❯

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development More ❯

Experience in SOME of the following predictive modelling techniques e.g. Logistic Regression, Log-Gamma GLMs, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Support Vector Machines and Neural Nets Experienced in the use of a programming language (e.g. R, Matlab, Python or Octave) Experience of using Emblem and Radar Highly numerate with excellent attention to detail Ability More ❯